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       <article class="post-6882 post type-post status-publish format-standard hentry category-multivariate category-data category-dmml category-packages category-software tag-rwordseg tag-423 tag-489 tag-634" id="post-6882">
        <header class="entry-header">
         <h1 class="entry-title">
          新浪微博文本分析初探v0.1
         </h1>
         <div class="entry-meta">
          <span class="date">
           <a href="http://cos.name/2013/01/analysis-of-weibo/" rel="bookmark" title="链向新浪微博文本分析初探v0.1的固定链接">
            <time class="entry-date" datetime="2013-01-13T13:58:12+00:00">
             2013/01/13
            </time>
           </a>
          </span>
          <span class="categories-links">
           <a href="http://cos.name/category/data/multivariate/" rel="category tag">
            多元统计
           </a>
           、
           <a href="http://cos.name/category/data/" rel="category tag">
            数据分析
           </a>
           、
           <a href="http://cos.name/category/data/dmml/" rel="category tag">
            数据挖掘与机器学习
           </a>
           、
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            统计软件
           </a>
           、
           <a href="http://cos.name/category/software/" rel="category tag">
            软件应用
           </a>
          </span>
          <span class="tags-links">
           <a href="http://cos.name/tag/rwordseg/" rel="tag">
            Rwordseg
           </a>
           、
           <a href="http://cos.name/tag/%e5%88%86%e8%af%8d/" rel="tag">
            分词
           </a>
           、
           <a href="http://cos.name/tag/%e5%be%ae%e5%8d%9a/" rel="tag">
            微博
           </a>
           、
           <a href="http://cos.name/tag/%e8%81%9a%e7%b1%bb/" rel="tag">
            聚类
           </a>
          </span>
          <span class="author vcard">
           <a class="url fn n" href="http://cos.name/author/bigknife/" rel="author" title="查看所有由郝智恒发布的文章">
            郝智恒
           </a>
          </span>
         </div>
         <!-- .entry-meta -->
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        <!-- .entry-header -->
        <div class="entry-content">
         <p>
          v0.1版本说明：本文发在主站上之后，站友们经常评论代码跑着有问题。经过和lijian大哥等人进行咨询，自己也摸索了一些之后，发现了之前代码非常多的漏洞。因此，给广大站友带来了困扰。在这里我表示万分的抱歉。最近邮箱中收到让我整理代码的需求越来越多。我也非常想整理下，但是由于工作也非常繁忙，所以很难抽出时间。前两天说5.1期间会整理一下代码发出来。但是事实上因为5.1小长假期间我可能无法上网，导致无力更新代码。所以今晚抽时间对代码进行了简单的修改。对本文也进行了一些调整。目前的状况是，基本上到生成待分析的语料库已经没有问题了。聚类分析的模型可以跑出来，但是最终的图画不出来。我暂时也没能找到原因。所以进一步的调整可能要等到5.1过完以后再抽时间来做了。这篇文章我会负责到底的哈。（20130429）
         </p>
         <p>
          完整代码如下：
          <a href="http://cos.name/2013/01/analysis-of-weibo/weibo_analysis/" rel="attachment wp-att-7753">
           weibo_analysis
          </a>
         </p>
         <p>
          —————————–分割线————————————————-
         </p>
         <p>
          自从lijian大哥的Rweibo包问世以来，便成了R爱好者们获取新浪微博数据的最为重要的工具。在该包的中文主页上，作者对如何连接新浪微博的API，获取授权，并以此为基础开发应用的原理讲解的非常清楚。对于我这种连基本的网页开发神马原理都一点也不清楚的菜鸟来说，Rweibo是一种非常趁手的获取微博数据的工具。
         </p>
         <p>
          有了获取数据的工具，对于中文文本分析来说，最重要的是分词。这里使用的分词算法来自中科院 ictclas算法。依然是沾了lijian大哥Rwordseg的光，直接拿来用了。
         </p>
         <p>
          有了这两样利器，我们便可以来分析一下新浪微博的数据了。我选取的话题是最近热映的国产喜剧电影《泰囧》，在微博上拿到了998条和“泰囧”有关的微博文本。代码如下（
          <del>
           以下代码不能直接执行，请首先阅读链接中Rweibo的关于授权帮助文档
          </del>
          ）：
         </p>
         <pre>#关键词搜索并不需要注册API
require(Rweibo)
#registerApp(app_name = "SNA3", "********", "****************")
#roauth &lt;- createOAuth(app_name = "SNA3", access_name = "rweibo")
res &lt;- web.search.content("泰囧", page = 10, sleepmean = 10,
           sleepsd = 1)$Weibo</pre>
         <p>
          获取了数据之后，首先迫不及待对微博文本进行分词。代码如下（Rwordseg包可以在语料库中自助加入新词，比如下面的insertWords语句）：
         </p>
         <pre>require(Rwordseg)
insertWords("泰囧")
n = length(res[, 1])
res = res[res!=" "]
words = unlist(lapply(X = res, FUN = segmentCN))
word = lapply(X = words, FUN = strsplit, " ")
v = table(unlist(word))
v = sort(v, decreasing = T)
v[1:100]
head(v)
d = data.frame(word = names(v), freq = v)</pre>
         <p>
          <span id="more-6882">
          </span>
          完成分词之后，我们最先想到的，便是对词频进行统计。词频排名前53的词列表如下（这个词频是我人工清理过的，但是只删除了一些符号）：
         </p>
         <p>
          泰囧 1174         一代宗师 87         时候 53          生活 44          娱乐 35          成功 30
          <br/>
          电影 385           看过 70                影片 52          文化 43          但是 33      王宝强 30
          <br/>
          票房 306          上映 68                 今天 51          影院 43          分享 33
          <br/>
          囧 275              泰国 68                喜剧 51          炮轰 40          发现 32
          <br/>
          笑 192              感觉 62                导演 49          电影院 38       故事 32
          <br/>
          俗 188              观众 61                好看 49          排 38              光线 32
          <br/>
          十二生肖 123   可以 60                喜欢 49           哈哈 37          国民 32
          <br/>
          什么 104          大家 59                上海 48           兽 37              时间 32
          <br/>
          中国 102          教授 56                现在 48           水平 37          哈哈哈 31
          <br/>
          徐峥 90            11亿 54                搞笑 47           需要 35         逼 30
          <br/>
          从中我们可以看出一些东西。比如说这部电影的口碑似乎还不错，此外某教授对其的炮轰也引发了不少得讨论。另外，同档期的另外两部电影（一代宗师，十二生肖）也经常和它同时被提及（这是否会对某些搞传播和营销的人带来一些启发，联动效应之类的，纯数个人瞎说）。 词云展示是不可少的，展示频率最高的150个词（这里我实现把分词的结果存放在了txt文件中，主要目的是为了节省内存）：
         </p>
         <pre>require(wordcloud)
d = read.table("wordseg.txt")
dd = tail(d, 150)
op = par(bg = "lightyellow")
# grayLevels = gray((dd$freq)/(max(dd$freq) + 140))
# wordcloud(dd$word, dd$freq, colors = grayLevels)
rainbowLevels = rainbow((dd$freq)/(max(dd$freq) - 10))
wordcloud(dd$word, dd$freq, col = rainbow(length(d$freq)))
par(op)</pre>
         <p>
          <a href="http://cos.name/wp-content/uploads/2013/01/Taijiong.png">
           <img src="http://cos.name/wp-content/uploads/2013/01/Taijiong.png"/>
          </a>
         </p>
         <p>
          下面做一些相对来说比较专业的文本挖掘的工作。主要目的是对这998条微博进行聚类。聚类里最核心的概念是距离。将距离比较靠近的数据聚为一类就是聚类。对于文本来说，如何定义距离呢？也就是说我如何来衡量微博与微博之间的距离。这涉及到了文本挖掘最基本的概念，通过建立语料库，词频-文档矩阵，来衡量文档之间的相关性，从而衡量文档之间的距离之类的。
          <a href="http://www.bjt.name/2012/03/text-mining-in-r/" target="_blank">
           详情请参看刘思喆大哥R语言环境下的文本挖掘
          </a>
          。下面使用PAM算法，对998条微博进行聚类。看看能不能得出一些什么有意思的结果。
         </p>
         <p>
          PAM算法全称是Partitioning Around Medoids算法。中文翻译为围绕中心点的划分算法。该算法是基于相异矩阵的（dissimilarity matrix）。也就是说，这个算法对于样本的距离度量是基于相异矩阵的。而不是基于通常使用的距离。因此，这个算法相对来说比较稳健（比起kmeans）。该算法首先计算出k个medoid，medoid的定义有点绕口。基本上的想法就是它和同一聚类中的其他对象的相异性是最小的。也就是说，同一个聚类的对象都是围绕着medoid的。和它的平均相异程度最小。找到这些medoid之后，再将其他样本点按照与medoid的相似性进行分配。从而完成聚类。R语言中的fpc包实现了这种算法，并且给出了非常有意思的聚类图。
         </p>
         <p>
          首先，载入tm包，建立语料库，建立词频矩阵:
         </p>
         <pre>#4.建立语料库
require(tm)
#先生成一个语料库，来清理一下微博的文本
weiboCorpus&lt;-Corpus(VectorSource(res))
#删除标点符号
weiboCorpus&lt;-tm_map(weiboCorpus,removePunctuation)
#删除数字
weiboCorpus&lt;-tm_map(weiboCorpus,removeNumbers)
#删除URL,使用了一点正则表达式
removeURL&lt;-function(x) gsub("http[[:alnum:]]*","",x)
weiboCorpus&lt;-tm_map(weiboCorpus,removeURL)
#再次分词
weiboData&lt;-as.data.frame(weiboCorpus)
weiboData&lt;-t(weiboData)
weiboData&lt;-as.data.frame(weiboData)
#head(weiboData) #再次加入一些词
insertWords(c("泰囧","十二生肖","一代宗师","黄渤","人在囧途","人再囧途","三俗"))
weiboData$segWord&lt;-segmentCN(as.matrix(weiboData)[,1])
#head(weiboData)
#形成了一个data.frame--weiboData，第一个变量为微博内容本身，第二个变量为分词的结果
#再次形成一个语料库，用来做更进一步的分析
weiboCorpusForAnys &lt;- Corpus(DataframeSource(weiboData))
#其实这个时候再画一个词云，可能效果会更好些
#目前代码运行到这一步都是没有问题的。我反复试了几次了。
#下面的fpc做聚类，最终图形无法展示出来。回头我5.1放假回来会扣一下的。</pre>
         <p>
          <code>
           <br/>
           #5.pam算法对微博进行聚类分析
           <br/>
           require(fpc)
           <br/>
           weiboTDMatrix control = list(wordLengths = c(1, Inf)))
           <br/>
           TDMforCluster&lt;-removeSparseTerms(weiboTDMatrix,sparse=0.9)
           <br/>
           MatrixForCluster&lt;-as.matrix(TDMforCluster)
           <br/>
           MatrixWeiboForCluster&lt;-t(MatrixForCluster)
           <br/>
           pamRes&lt;-pamk(MatrixWeiboForCluster,metric="manhattan")
           <br/>
           k&lt;-pamRes$nc
           <br/>
           k
           <br/>
           pamResult&lt;-pamRes$pamobject
           <br/>
           pamResult$clustering
           <br/>
           layout(matrix(c(1,2),2,1))
           <br/>
           plot(pamResult,color=F,labels=4,lines=0,cex=0.8,col.clus=1,col.p=pamResult$clustering)
           <br/>
           layout(matrix(1))
          </code>
          <br/>
          结果我们将微博分成了两类：
         </p>
         <p>
          <a href="http://cos.name/wp-content/uploads/2013/01/Taijiong-Clustering.png">
           <img src="http://cos.name/wp-content/uploads/2013/01/Taijiong-Clustering-500x117.png"/>
          </a>
         </p>
         <p>
          当然了，从这个图，你很难看出点什么有益的信息，就是图个好看。我们不妨来看看被分成两类的微博都分别说了些什么。具体看到过程和解读因人而异，这里也没什么代码要列出来。我只说一些我看到的，不保证是对的。
         </p>
         <p>
          两个聚类中的微博讨论的问题不同，第一类讨论的是看了泰囧的心情，比如开心，高兴抑或难过之类的。比如：
         </p>
         <blockquote>
          <p>
           “哈哈哈二到無窮大.大半夜的我這二逼在家看泰囧.笑到爸爸起床罵我..不好意思咧.實在沒忍住”
          </p>
         </blockquote>
         <blockquote>
          <p>
           “时间滴答滴答的走我知道我在想着一个人看泰囧片头的时候熟悉的名字我一下子愣住了我想我是在乎了这样的夜里我难过”
          </p>
         </blockquote>
         <blockquote>
          <p>
           “大半夜睡不着觉一个人在家看盗版泰囧突然觉得很凄惨”
          </p>
         </blockquote>
         <blockquote>
          <p>
           “我们一起吃牛排一起坐轮渡一起看金门一起去乐园一起吃牛排一起看大海一起坐公交一起啃鸡爪一起过圣诞一起看泰囧一起去鼓浪屿一起打的绕厦门岛一起在酒店吃早餐一起在一张大床上睡觉一起吃烤鱼一起在大排档吃肉一起在KFC买了对辣翅一起爬鼓山一起抱着对方说我爱你”
          </p>
         </blockquote>
         <p>
          这一类微博本身不够成对电影的评价，电影是这些博主生活的一部分，或悲或喜，电影只是陪衬。
         </p>
         <p>
          第二类微博，则集中于对电影的评价，褒贬不一，比如：
         </p>
         <blockquote>
          <p>
           “搜索一代宗师发现十个里面九个说不好看上回的泰囧微博上都是说怎么怎么好笑结果去影院一看大失所望还没有赵本山演的落叶归根幽默和寓意深远纯属快餐式电影其实好的事物往往具有很大的争议性就比如John.Cage.的有的人觉得纯属扯淡有的人却如获至宝我想王家卫的电影也是如此”
          </p>
         </blockquote>
         <blockquote>
          <p>
           “应该看第一部人在囧途比泰囧好看太多了第一部我从头看到尾很有意思第二部看分钟掐断沉闷没什么笑点”
          </p>
         </blockquote>
         <blockquote>
          <p>
           “泰囧实在好看极了又搞笑又感动让我哭笑不得真心推荐晚安啦.我在”
          </p>
         </blockquote>
         <blockquote>
          <p>
           “发表了博文.影评人再囧途之泰囧..首映没有赶上好多朋友强烈向我推荐推荐理由很具有唯一性笑到我抽搐.笑成了这部电影唯一的标签但是这已经足够了.在好莱坞大片冲击欧洲小资”
          </p>
         </blockquote>
         <p>
          从我的解读来看，微博大致分为这两类，如果进一步分析，也可以将发微博的人分成两类。一类可能相对感性，单纯，生活中的高兴或者快乐，会表现在微博中。电影只是作为引发他们情绪的一件事儿被提及。而另一类人，相对比较理性，喜欢评论，喜欢写博客写影评之类。电影在他们的心中，是被评价的对象。当然，这两类人或者两类微博会有很多部分是重叠交替的。这是非常正常的现象，就像人也有理性和感性的两个面。
         </p>
         <p>
          结语：本文仅仅是对微博数据的初步探索。感谢lijian大哥的两个包，我想，这两个包将改变微博数据分析的面貌。更多R语言爱好者将通过这两个包发挥他们的热情，来更多的挖掘微博中有价值的信息。另外，笔者从未深入研究过文本挖掘。望看官拍砖时手下留情。
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         《
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          新浪微博文本分析初探v0.1
         </span>
         》有64个想法
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               2013/01/14 02:34
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            <p>
             赞图形，顺便求解为啥我的中文词云画出来就是乱码？…伤心。
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                bigknife
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                <time datetime="2013-01-14T21:35:09+00:00">
                 2013/01/14 21:35
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              <p>
               是不是因为编码的问题？试试iconv(x,”utf-8″,”gbk”)？
               <br/>
               其中x是你要输出的对象。
              </p>
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                   2013/01/17 15:40
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                <p>
                 无论是GBK还是UTF-8都是乱码…只不过前者不可读而后者直接是这种…莫不是跟我把locale设成utf8_en_US有关？
                </p>
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                  梁婧
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                  <time datetime="2016-05-14T19:58:01+00:00">
                   2016/05/14 19:58
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                <p>
                 我现在正在做电影微博评论的情感分析，遇到一些问题，可以请教一下你吗？可否加我qq1305919043
                </p>
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               paris
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               2013/01/14 10:00
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            <p>
             哇把李舰大哥的精华都应用上了
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                 2013/01/14 10:53
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              <p>
               弄个舰哥粉丝团神马的…
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              dzw259
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               2013/01/15 10:15
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            <p>
             认真学习ing
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            <p>
             我也想尝试下rweibo，请问下 你是在R版本2.10.1和JDK1.6的环境下操作成功的吗，因为我的R版本为2.15.2 它提示我无法使用rJava；能提供下邮箱么，这样交流起来方便些
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                bigknife
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                 2013/01/19 21:24
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               我猜可能是你电脑上没安装java吧。
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                <p>
                 说的是JER么。。。
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              龚牟利
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               2013/01/23 00:23
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            <p>
             看来对于我们学传播学的帮助很大
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             <b class="fn">
              He
             </b>
             <span class="says">
              说道：
             </span>
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-3639">
              <time datetime="2013-01-25T09:30:26+00:00">
               2013/01/25 09:30
              </time>
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            <p>
             res &lt;- web.search.content("泰囧", page = 50, sleepmean = 10,
             <br/>
             sleepsd = 1)$Weibo
            </p>
            <p>
             求助：用这一句搜索内容的时候速度非常非常慢，page=1都要好几分钟才能打开，怎么回事
            </p>
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            <a aria-label="回复给He" class="comment-reply-link" href="http://cos.name/2013/01/analysis-of-weibo/?replytocom=3639#respond" onclick='return addComment.moveForm( "div-comment-3639", "3639", "respond", "6882" )' rel="nofollow">
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               <b class="fn">
                bigknife
               </b>
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                说道：
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               <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-3640">
                <time datetime="2013-01-26T18:36:25+00:00">
                 2013/01/26 18:36
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              <p>
               这个应该和网络状况有关吧我觉得。有多慢呢？page=1的情况下大概花了多长时间？
              </p>
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             <b class="fn">
              paris
             </b>
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-3641">
              <time datetime="2013-01-28T16:43:32+00:00">
               2013/01/28 16:43
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            <p>
             &gt; res &lt;- web.search.content("泰囧", page = 10, sleepmean = 10,sleepsd = 1)$Weibo
             <br/>
             错误于fromJSON(weibojson) :
             <br/>
             CHAR() can only be applied to a 'CHARSXP', not a 'NULL'
            </p>
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            <a aria-label="回复给paris" class="comment-reply-link" href="http://cos.name/2013/01/analysis-of-weibo/?replytocom=3641#respond" onclick='return addComment.moveForm( "div-comment-3641", "3641", "respond", "6882" )' rel="nofollow">
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               <b class="fn">
                bigknife
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               <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-3656">
                <time datetime="2013-02-02T11:22:46+00:00">
                 2013/02/02 11:22
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              <p>
               这个问题遇到多次了，换个机器试试
              </p>
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              <a aria-label="回复给bigknife" class="comment-reply-link" href="http://cos.name/2013/01/analysis-of-weibo/?replytocom=3656#respond" onclick='return addComment.moveForm( "div-comment-3656", "3656", "respond", "6882" )' rel="nofollow">
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               <b class="fn">
                Veronica.C
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               <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-3952">
                <time datetime="2013-04-10T03:41:31+00:00">
                 2013/04/10 03:41
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              <p>
               这是因为你超过新浪下载的限制了，需要停一段时间再下
              </p>
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              <a aria-label="回复给Veronica.C" class="comment-reply-link" href="http://cos.name/2013/01/analysis-of-weibo/?replytocom=3952#respond" onclick='return addComment.moveForm( "div-comment-3952", "3952", "respond", "6882" )' rel="nofollow">
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             <b class="fn">
              wyf
             </b>
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              说道：
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-3698">
              <time datetime="2013-02-15T10:26:13+00:00">
               2013/02/15 10:26
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            <p>
             Rweibo已经抓取成功，res内也包括了我想要的内容，但是在Rwordseg 使用的你的代码处理的时候最终结果都是字和每个字的freq，求指导啊！！但是我在
             <br/>
             &gt; require(Rwordseg)
             <br/>
             &gt; segmentCN(“钓鱼岛是中国的，苍井空是大家的”)
             <br/>
             [1] “钓鱼岛” “是”     “中国”   “的”     “苍井空” “是”     “大家”   “的”
             <br/>
             这样是没问题的，我对字符型数据的处理似乎有点问题
            </p>
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             <b class="fn">
              Drewry
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               2013/02/21 11:26
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            <p>
             你好！我在使用words=unlist(lapply(X=res, FUN=segmentCN))之后，words得到的是乱码(感觉像是把中文编码给拆开来了)，请问有解决方法吗？
             <br/>
             另外，如果楼主方便的话，是否能在编码后面添加简单的注释？谢谢
            </p>
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              Drewry
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              <time datetime="2013-02-21T11:33:22+00:00">
               2013/02/21 11:33
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            <p>
             LZ辛苦了。请问个问题，我使用words=unlist(lapply(X=res, FUN=segmentCN))之后，得到的结果是乱码(感觉像是中文编码被拆分开来了)，请问应该如何解决？
            </p>
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                bigknife
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                 2013/02/21 18:58
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              <p>
               趴下来的数据本身是正常的吗？还是说分词以后变成乱码了？
              </p>
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                  Drewry
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                  <time datetime="2013-02-23T03:36:33+00:00">
                   2013/02/23 03:36
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                <p>
                 趴下来的数据是正常的，如果直接用segmentCN对趴下来的数据进行分词也是正常的。但是如果用words=unlist(lapply(X=res2, FUN=segmentCN))对数据进行分词，就不正常了。
                </p>
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               <b class="fn">
                bigknife
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                说道：
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               <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-3757">
                <time datetime="2013-02-27T12:12:33+00:00">
                 2013/02/27 12:12
                </time>
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              <p>
               这个问题就不太清楚了，莫非和lapply有关吗？搭车看看有没有高人出来解答一下吧
              </p>
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             <b class="fn">
              <a class="url" href="http://weibo.com/u/1997763905" rel="external nofollow">
               代冕
              </a>
             </b>
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              说道：
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              <time datetime="2013-03-04T19:11:51+00:00">
               2013/03/04 19:11
              </time>
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            <p>
             今天试了一天Rweibo，但在授权网页老是出现redirect_uri_mismatch错误，原来是注册授权时少个步骤，解决步骤可查看
             <br/>
             <a href="http://qqy620.diandian.com/post/2012-09-20/40039410248" rel="nofollow">
              http://qqy620.diandian.com/post/2012-09-20/40039410248
             </a>
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               <b class="fn">
                郝智恒
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                <time datetime="2013-03-05T12:49:08+00:00">
                 2013/03/05 12:49
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              <p>
               感谢分享
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               <b class="fn">
                causu
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                <time datetime="2013-03-13T12:45:25+00:00">
                 2013/03/13 12:45
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              <p>
               呃。也碰到这个问题，看你的网页也是一头雾水啊
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              F0532
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              <time datetime="2013-03-16T18:46:55+00:00">
               2013/03/16 18:46
              </time>
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            <p>
             感谢分享，学习了
            </p>
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             <b class="fn">
              yuanyuan
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               2013/03/16 23:05
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            <p>
             您好，我时华师统计研二，可否交个朋友？曾在医院实习一年，现在在电子商务公司实习，比较感兴趣的领域： 社交网络数据分析，统计可视化，序贯，纵向数据分析。
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                Will
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                <time datetime="2013-04-23T11:48:43+00:00">
                 2013/04/23 11:48
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               楼主共享这些代码已经不错了，其他的自己去学习添加吧
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              yuanyuan
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              <time datetime="2013-03-17T14:11:20+00:00">
               2013/03/17 14:11
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            <p>
             今天在运行：
             <br/>
             roauth &lt;- createOAuth(app_name = "R微博数据分析", access_name = "秋恋sunshine",forcelogin = TRUE)后弹出网页显示输入用户名和密码，但是之后网页就显示：已取消到该网页的导航。得不到授权的密码，这是为什么呢？
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              yangchen
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-3826">
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               2013/03/18 18:54
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            <p>
             weiboCorpusForAnys # 生成文档-词条矩阵，请问是如何生成的？是不是少了一行代码啊？
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                bigknife
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                 2013/03/19 08:48
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              <p>
               是少了一行代码。近期我得重新整理一下本文的代码。多谢提醒。
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              Rfans
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               2013/03/25 21:55
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            <p>
             LZ,你好，我在运行这个代码的时候出现些错误，你帮忙看一下吧，谢谢！
             <br/>
             1.n = length(res[, 1]) 显示量度数目不对；
             <br/>
             2.v = sort(v, deceasing = T) 无法执行降序排列；
             <br/>
             3.&gt; rainbowLevels = rainbow((dd$freq)/(max(dd$freq) – 10))
             <br/>
             错误于if ((n  0) { :
             <br/>
             需要TRUE/FALSE值的地方不可以用缺少值
             <br/>
             此外: 警告信息：
             <br/>
             In max(dd$freq) : max里所有的参数都不存在；回覆-Inf
             <br/>
             为什么词云显示不出来？
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              Rfans
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               2013/03/28 10:43
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            <p>
             LZ好！我在用你的代码做聚类时，总是显示
             <br/>
             layout(matrix(c(1,2),2,1)) 图像无法显示
             <br/>
             plot(pamResult,color=F,labels=4,lines=0,cex=0.8,col.clus=1,col.p=pamResult$clustering)
             <br/>
             错误于princomp.default(x, scores = TRUE, cor = ncol(x) != 2) :
             <br/>
             cannot use cor=TRUE with a constant variable
            </p>
            <p>
             然后 layout(matrix(1))  出不来下面的分类图
             <br/>
             请问怎么解决呢?
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             <b class="fn">
              Veronica.C
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              <time datetime="2013-04-10T03:59:58+00:00">
               2013/04/10 03:59
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            <p>
             求问weiboCorpusForAnys代码！谢谢楼主~~~
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                李青龙
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                 2013/04/10 08:15
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              <p>
               我是觉得从那句后面之后就无法运行了。。。
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                  Veronica.C
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                   2013/04/16 00:38
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                <p>
                 是啊，是这样的。。
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              dayuad
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              <time datetime="2013-04-15T20:47:46+00:00">
               2013/04/15 20:47
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            <p>
             强烈建议楼主，从新整理一下代码，让我们可以学习！！
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              Veronica.C
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               2013/04/16 00:41
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            <p>
             除了盼望楼主加上那句以外。。。
             <br/>
             还有这句：（这个词频是我人工清理过的，但是只删除了一些符号）
            </p>
            <p>
             楼主肯定手动删除了，我，的，看 这样的词语
             <br/>
             在英文里这些叫stopword是可以用tm包自动删除的，中文有没有类似匹配的东西呢？谢谢啦
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              xccds
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              <time datetime="2013-04-16T21:37:59+00:00">
               2013/04/16 21:37
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            <p>
             赫兄弟的代码没写得很清楚，实际上处理中文的流程有些不一样的，有好几个人都跑来问我tm为啥出错，估计都是看你的代码被坑了。如果是先分词，再进tm包建立corpus就不会出错。
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                bigknife
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                <time datetime="2013-04-16T21:45:21+00:00">
                 2013/04/16 21:45
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              <p>
               我这个代码缺失了一部分，所以有很多人来问。不过我最近事儿实在事儿太多了，过一阵子我会重新整理一下代码。各位实在是对不住了。
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                 <b class="fn">
                  Veronica.C
                 </b>
                 <span class="says">
                  说道：
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                 <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4052">
                  <time datetime="2013-04-19T02:31:30+00:00">
                   2013/04/19 02:31
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                <p>
                 楼主辛苦，静等楼主更新：）
                </p>
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             <b class="fn">
              Will
             </b>
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              说道：
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4084">
              <time datetime="2013-04-23T13:16:37+00:00">
               2013/04/23 13:16
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            <p>
             郝兄弟，代码赶快重新整理一下，都说是tm包的问题啊
            </p>
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               <b class="fn">
                bigknife
               </b>
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               <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4098">
                <time datetime="2013-04-26T18:34:36+00:00">
                 2013/04/26 18:34
                </time>
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              <p>
               当时第一版代码是发在人人网上，那一版貌似是全的。后来转到豆瓣上的时候就少了一些，再放在统计之都的时候就又乱掉了。这个还是我的能力问题啊。我争取5.1假期期间把代码整理出来，并且进行一些更新。文章发在主站上，我会负责到底的。：）
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             <b class="fn">
              Rest
             </b>
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              说道：
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4091">
              <time datetime="2013-04-24T13:43:06+00:00">
               2013/04/24 13:43
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            <p>
             强烈建议楼主重新整理代码！
            </p>
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             <b class="fn">
              <a class="url" href="http://ningoo.net" rel="external nofollow">
               NinGoo
              </a>
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              <time datetime="2013-05-02T21:57:11+00:00">
               2013/05/02 21:57
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            <p>
             v&lt;-sort(v,deceasing=T)
             <br/>
             应该是
             <br/>
             v&lt;-sort(v,decreasing=T)
            </p>
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               <b class="fn">
                郝智恒
               </b>
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               <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4162">
                <time datetime="2013-05-05T16:32:36+00:00">
                 2013/05/05 16:32
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              <p>
               多谢,已改正
              </p>
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             <b class="fn">
              chen
             </b>
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4177">
              <time datetime="2013-05-09T17:26:47+00:00">
               2013/05/09 17:26
              </time>
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            <p>
             你们说的Rweibo软件在哪下啊
            </p>
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             <b class="fn">
              yang
             </b>
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4319">
              <time datetime="2013-06-01T19:07:39+00:00">
               2013/06/01 19:07
              </time>
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            <p>
             两类是自定的吗？
            </p>
            <p>
             PAM有什么可以检验k值大小的方法没？
            </p>
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              yang
             </b>
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4320">
              <time datetime="2013-06-01T20:29:47+00:00">
               2013/06/01 20:29
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            <p>
             为啥不用cluster包嘞？感觉比较好用诶。pam适合大数据么，clara是否更好？
            </p>
            <p>
             有问题的码是分词的事情，好像不是clustering的问题吧？
            </p>
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             <b class="fn">
              shang00122
             </b>
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              <time datetime="2013-06-03T06:50:05+00:00">
               2013/06/03 06:50
              </time>
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            <p>
             &gt;plot(pamResult,color=F,labels=4,lines=0,cex=0.8,col.clus=1,col.p=pamResult$clustering)
             <br/>
             Error in princomp.default(x, scores = TRUE, cor = ncol(x) != 2) :
             <br/>
             cannot use ‘cor = TRUE’ with a constant variable
             <br/>
             请教各位大侠，这是什么原因呢？
            </p>
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             <b class="fn">
              冷冷
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4351">
              <time datetime="2013-06-07T15:30:05+00:00">
               2013/06/07 15:30
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            <p>
             &gt; install.packages(“Rwordseg”)
             <br/>
             警告信息：
             <br/>
             package ‘Rwordseg’ is not available (for R version 3.0.1)
             <br/>
             &gt;
            </p>
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               <b class="fn">
                golay
               </b>
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               <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-6836">
                <time datetime="2015-09-02T16:50:02+00:00">
                 2015/09/02 16:50
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              <p>
               你是不是在Mac  rstudio里面安装的啊？要在R中安装就不会报错了，然后再在rstudio 里面library调用即可。
              </p>
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           Pingback：
           <a class="url" href="http://wulujia.com/?p=7" rel="external nofollow">
            Mac下R语言wordcloud输出中文乱码 | notepad
           </a>
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             <b class="fn">
              spzmoon
             </b>
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-4987">
              <time datetime="2013-10-21T11:13:11+00:00">
               2013/10/21 11:13
              </time>
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            <p>
             我也出现了一样的错误！！！有解决方案么
            </p>
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             <b class="fn">
              <a class="url" href="http://weibo.com/qq642215039" rel="external nofollow">
               _裸渀的蜗牛_
              </a>
             </b>
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              说道：
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              <time datetime="2013-12-30T20:25:58+00:00">
               2013/12/30 20:25
              </time>
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            <p>
             过了很多天了，从新抓取还是不行
            </p>
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            <a aria-label="回复给_裸渀的蜗牛_" class="comment-reply-link" href="http://cos.name/2013/01/analysis-of-weibo/?replytocom=5211#respond" onclick='return addComment.moveForm( "div-comment-5211", "5211", "respond", "6882" )' rel="nofollow">
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             <b class="fn">
              <a class="url" href="http://t.qq.com/laccccrrr" rel="external nofollow">
               陈雨涵
              </a>
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-6217">
              <time datetime="2014-09-17T12:21:03+00:00">
               2014/09/17 12:21
              </time>
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             请问一下，这里它需要说是 rJava 包，我下载了，也安装了。就是没有载入这是怎么回事？？？？
            </p>
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              <a class="url" href="http://weibo.com/5271808816" rel="external nofollow">
               用户5271808816
              </a>
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              说道：
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               2014/10/12 14:41
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             楼主，请问一下代码是不是还有错误，不知道整理好了没？
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             <b class="fn">
              我是游客
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               2014/12/22 15:11
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            <p>
             你好 请问Rweibo这个包现在还可以用吗？为什么我在关键词搜索的时候就出错了，没有内容
             <br/>
             res&lt;-web.search.content("R语言",page=2,)
             <br/>
             1 pages was stored!
             <br/>
             警告信息：
             <br/>
             In web.search.content("R语言", page = 2, ) : Error in page 1
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                成百
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                 2015/04/14 13:15
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              <p>
               同问！！你现在有解决方案吗
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              成百
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            <p>
             res &lt;- web.search.content("泰囧", page = 10, sleepmean = 10,
             <br/>
             +            sleepsd = 1)$Weibo
             <br/>
             1 pages was stored!
             <br/>
             警告信息：
             <br/>
             In web.search.content("泰囧", page = 10, sleepmean = 10, sleepsd = 1) :
             <br/>
             Error in page 1
             <br/>
             请问怎么解决，谢谢
            </p>
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              成百
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               2015/04/14 13:14
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            <p>
             获取数据不成功
            </p>
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             <b class="fn">
              yonghu
             </b>
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             <a href="http://cos.name/2013/01/analysis-of-weibo/#comment-6790">
              <time datetime="2015-07-29T14:25:27+00:00">
               2015/07/29 14:25
              </time>
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            <p>
             怎么微博数据获取不成功啊
            </p>
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              素还真
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               2015/11/26 14:10
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             劣者也是Error in page 1，求解决方案
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              Tiffany
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               2015/12/29 13:08
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            <p>
             &gt; library(tm)
             <br/>
             &gt; test test test
             <br/>
             &gt; testdata&lt;-as.data.frame(test)
             <br/>
             Error in as.data.frame.default(test) :
             <br/>
             不能把"c("VCorpus", "Corpus")"类别强迫变成数据框
            </p>
            <p>
             求助这种情况应该怎么处理
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